线性矩法估计参数的保证修正值系数B的推求

在设计洪水的抽样误差估计中,采用保证修正值系数B方法估计均方差简单易用。应用线性矩法估计频率分布曲线的参数,有较好的无偏性和有效性,具有一定的应用前景。目前线性矩法的B值诺模图尚未确定,给用线性矩法确定参数时估计抽样误差带来了难度与不便。采用统计试验,分析了离差系数、偏态系数和样本长度对B值的影响,结果表明线性矩法估计参数时仍可采用保证修正值系数B值诺模图方法来估计抽样误差,并推求了不同偏态系数、设计频率情形下的B值,制成了线性矩法的B值诺模图备用。     

Angular resolution of terrestrial laser scanners

Knowledge of a laser scanner's spatial resolution is necessary in order to prevent aliasing and estimate the level of detail that can be resolved from a scanned point cloud. Spatial resolution can be decoupled into range and angular components. The latter is the focus of this paper and is governed primarily by sampling interval and laser beamwidth. However, emphasis is often placed on one of these—typically sampling interval—as an indicator of resolution. Since both affect the resolution of a scanned point cloud, consideration of only one factor independent of the other can lead to a misunderstanding of a system's capabilities. This will be demonstrated to be inappropriate except under very specific conditions. A new, more appropriate resolution measure for laser scanners, the effective instantaneous field of view (EIFOV), is proposed. It is derived by modelling the shift variance of the equal angular increment sampling process, laser beamwidth-induced positional uncertainty and observed angle quantisation with ensemble average modulation transfer functions (AMTFs). Several commercially available terrestrial laser scanner systems are modelled and analysed in terms of their angular resolution capabilities using the EIFOV.     

高密度空间采样地震数据特点分析

中国陆相沉积盆地的地质结构复杂,储层岩性的多变,需要有高精度的勘探方法。高密度空间采样是提高地震勘探精度的一项新技术。本文简要说明了点激发和点接收技术,分析高密度空间采样的野外工作方法,介绍了Gijs j．o．Vermeer提出的对称采样原理,从波场连续性的角度探讨了高密度空间采样技术。重点分析高密度空间采样数据的特点, 即:高密集的初至波有利于近地表结构的调查,可提高静校正的精度;小偏移距、小点距接收增加了浅层的有效覆盖次数,提高浅层反射的成像精度; 对规则噪声可实现无假频采样,室内的噪声分析和噪声压制的精度随着提高;高密度采集使波场连续性增强,使得各种数学变换的精度提高,有利于不同波场的分离。最后指出高密度空间采样地震勘探技术的难点在于室内数据处理,针对海量数据的分析和处理方法还需要进行深入细致的研究工作。     

Efficiency of kriging estimation for square, triangular, and hexagonal grids

Although several researchers have pointed out some advantages and disadvantages of various soil sampling designs in the presence of spatial autocorrelation, a more detailed study is presented herein which examines the geometrical relationship of three sampling designs, namely the square, the equilateral triangle, and the regular hexagon. Both advantages and disadvantages exist in the use of these designs with respect to estimation of the semivariogram and their effect on the mean square error or variance of error. This research could be used to design optimal sampling strategies; it is based on the theory of regionalized variables, in which the intrinsic hypothesis is satisfied. Among alternative designs, an equilateral triangle design gives the most reliable estimate of the semivariogram. It also gives the minimum maximum mean square error of point estimation of the concentration over the other two designs for the same number of measurements when the nugget effect is small relative to the variance. If the nugget effect is large (.90 ² or more), and the linear sampling density is >0.85r where r is the range, the hexagonal design is best. This study computes and compares the maximum mean square error for each of these designs.     

基于MATLAB的基本矩阵随机采样鲁棒估计

基本矩阵的估算可以分为线性算法、非线性优化迭代算法、鲁棒估计算法三大类,而以鲁棒估计效率、效果最为突出,但是实现比较复杂。本文通过数码相机获取的两张未标定照片,采样互相关系数法和RANSAC算法,在MATLAB中实现了基本矩阵的自动拟合,实验表明拟合精度较高、速度快,为下一步三维场景的自动重建和量测奠定了基础。     

T -distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they are layer specific and include uncertainty caused by using variance estimates.     

时空多点连续定向取心技术应用研究

为解决以往定向仪不抗振、岩样采取率不高等问题，利用时间与钻孔空间位置对应的关系，研制成功了KD型定向仪。详细介绍了该定向仪的基本构成、技术参数及现场应用情况。     

基于规则格网的DEM插值实验

通过地形建模,将6个地形隶属函数按照101×101,112×112,126×126,144×144,168×168,201×201,257×257 7种格网密度生成6种局部地形单元的规则格网DEM;使用反距离加权(IDW)等7种插值算法,将前6种格网密度下的DEM插值成257×257规格;从原始257×257DEM中随机抽取检查点计算残差,并对残差中误差进行分析。通过分组插值实验,运用控制变量法、方差分析等方法研究地貌类型、采样密度和插值算法对DEM插值精度的影响。     

线性抽样及分形理论在景观异质性研究中的应用

景观异质性是景观生态学研究的核心,对景观格局、动态和功能具有决定作用。将线性抽样与分形理论相结合的方法应用于景观空间异质性的表达中,相比于传统方法,可以定量表达景观类型在空间序列中的组合规律,而该组合规律可以作为指标来测度景观空间异质性的高低。景观类型在空间序列中的组合越复杂,则景观的空间异质性越高。该方法以景观类型空间序列的线形图像为基础,利用分形理论计算线形图像的分维,以分维数值的大小来表达景观空间异质性的高低。但样线的布设方法、分维计算方法以及景观分类系统的不同都会对分维数值产生影响。以妫水河流域为试验区,对该方法的适用性进行验证,结果表明,该方法可以有效表达景观空间异质性的高低。